吉林化工学院本科毕业设计（论文）外文翻译
1.2 Assembly line
Assembly lines are similar to the flow shops in which assembly of parts are carried out in a line sequence. In a multi product assembly line, the sequencing of the jobs is a challenging task. Drexl et al. [16] considered an assembly line sequencing mixed model problem. It is a combinatorial problem. They formulated this combinational problem as integer programming model. This model can be used only for small size problems due to the limitations of operations research software with respect to handling the number of variables and constraints, which are present in the integerprogramming model. Xiaobo et al. [94] have considered similar work on mixed model assembly line sequencing problem with conveyor stoppages. They proposed branch and bound algorithm, and simulated annealing algorithm for finding the optimal solution and sub-optimal solution of the mixed-model sequencing problem, respectively to minimize the total conveyor stoppage time. The branchand- bound method was devoted to find the optimal solution of small-sized problems, whereas the simulated annealing method was used to cope with large-scale problems to obtain a good sub-optimal solution. Future, research on simulated annealing applied to this problem can be directed to establish a better seed generation algorithm. However, the practitioner should spend considerable time in fixing the parameter called temperature (T) in the simulated annealing algorithm by trail and error method before actually solving the problem.
1.3 Batch production system
In a batch production system, the switching over from one product to other product depends on many factors such as stock reaching to the threshold level, different priority schemes, economical setups, etc. Tafur Altiok et al. [86] have dealt this issue differently for the pull type
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吉林化工学院本科毕业设计（论文）外文翻译
manufacturing system with multi product types. In this paper, they developed an iterative procedure to approximately compute the average inventory level of each product as finished goods using different priority schemes. In this paper, the demand arrival process is assumed to be a poisson distribution and processing times and the set-up times are arbitrarily distributed. But, in practice, the processing times may follow other distributions, viz., normal, uniform, exponential, etc. which are not experimented in this paper. Khan et al. [35] addressed the problem of manufacturing system that procures raw materials from vendors in lot and convert them into finished products. They estimated production batch sizes for JIT delivery system and designed a JIT raw material supply system. A simple algorithm was developed to compute the batch sizes for both manufacturing and raw material purchasing policies.
2. JIT integration, implementation and benefits
Just-in-time is a manufacturing philosophy by which an organization seeks continuous improvements. For ensuring continuous improvements, it is necessary for any organization to implement and integrate the JIT and JIT related areas. If it is practiced in its true sense, the manufacturing performance and the financial performance of the system will definitely improve.
Swanson et al. [83] have reiterated that proper planning is essential for implementation of a JIT manufacturing system and a commitment from top management is a prerequisite. Cost benefit analysis is to be studied initially with the knowledge of key items such as the cost of conversion to a JIT system and time period of conversion. Cook et al. [11], in their case study for applying JIT in the continuous process industry, show improvements in demand forecast and decrease in lead-time variability.
The relationship between implementation of TQM, TPM and JIT will lead to improvement in the manufacturing performance (Kribty et al. [37]). Further Huang [23] discusses the importance of
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吉林化工学院本科毕业设计（论文）外文翻译
considering the integration of TPM, JIT, Quality control and FA (Factory Automization). Imai [27] believes that TQM and TPM are the two pillars supporting the JIT production system. Kakuro Amasaka [32] proposes a new JIT management system, which helps to transfer the management technology into management strategy.
Fullerton et al. [65] have conducted a study in 253 firms in USA to evaluate empirically whether the degree with which a firm implements the JIT practices affects the firms financial performance. From their study, JIT manufacturing system will reap sustainable rewards as measured by improved financial performance. Also, they studied the benefits of JIT implementation in 95 firms in USA. They have concluded that JIT implementation improves the performance of the system, because of resultant quality benefits, time based benefits, employees flexibility, accounting simplification, firms profitability and reduced inventory level.
3.Conclusion
The growing global competition forces many companies to reduce the costs of their inputs so that the companies can have greater profit margin. There are considerable advancements in technology and solution procedures in reality, to achieve the goal of minimizing the costs of inputs. JIT-KANBAN is an important system, which is used in production lines of many industries to minimize work-in-process and throughput time, and maximize line efficiency. In this paper, the authors have made an attempt to review the state-of-art of the research articles in the area “JIT-KANBAN system”. After a brief introduction to push and pull systems, different types of kanban and their operating principles, blocking mechanisms, the authors have classified the research articles under JIT-KANBAN system into five major headings, viz., empirical theory, modeling approach, variability and its effect, CONWIP and JIT-SCM. Also, the authors have provided a section for special cases under JIT-KANBAN. This paper would help the researchers to
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吉林化工学院本科毕业设计（论文）外文翻译
update themselves about the current directions and different issues under JIT-KANBAN system, which would further guide them for their future researches.
The directions for future researches are presented below.
The flow shop as well as mixed model assembly line problems come under combinatorial category. Hence, meta-heuristics viz., simulated annealing, genetic algorithm and tabu search may be used to find solution to determine the minimum number of kanbans and other measures. In simulated annealing algorithm, researchers can aim to device a better seed generation algorithm which will ensures better starting solution. In most of the papers, comparisons are done only based on relative improvements. Instead of this approach, comparisons based on complete ANOVA experiments would provide reliable inferences.
This algorithm developed by Elizabeth Vergara et al. [18] uses only two-point crossover genetic operators. A third genetic operator may be introduced to further improve the performance of the evolutionary algorithm. The evolutionary algorithm may be modified to handle complex supply chain problem. In JIT-SCM related research works, effort should be directed to develop simulation as well as meta-heuristics to derive results under probabilistic conditions.
In the work of Sarah M. Rayan et al. [69], the application of single chain analysis for multiple chain operation raises an open question whether a single WIP level should be maintained for all products or individual levels for each product. Further, most of the studies use simulation. Hence, future research shall be directed to develop improved search procedures for finding WIP levels in kanban systems. As an extension to the work of Krieg et al. [38], a decomposition algorithm can be developed for multiproduct kanban systems with state dependent setups. The adaptive approach suggested by Tardif et al. [85] may be extended for multi-stage, multi-product kanban system. The work of Lai et al. [41] can be extended by including more variables and elements and conducting
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吉林化工学院本科毕业设计（论文）外文翻译
experiments to investigate the stability of the system under various conditions such as the sudden increase in demand and random demand, experimenting on the system behaviour of different types of customer and modes of manufacturing. The nested partitioned method provided by Leyuan Shi and Shuli Men [43] can be enhanced by incorporating any one or a combination of the many other heuristics viz., elaborate partitioning, sampling, backtracking scheme, simulation, etc. Then, they can be applied to combinatorial problems of this type
Ants colony optimization algorithm is a recent inclusion to the existing meta-heuristics viz., simulated annealing algorithm, genetic algorithm and tabu search. So, a researcher can study the solution accuracy as well as required computational time of this algorithm for his/her JIT problem of interest, which falls under combinatorial category and compare its results with the results of the other three heuristics (meta-heuristics).
Source: C.Sendil Kumar, R.Panneerselvam, 2007.“Literature review of JIT-KANBAN system”.The
International
Journal
of
Advanced
Manufacturing
Technology,
vol.32,no.5,August.pp.393-408.
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